Development of pH-responsive Eudragit S100-functionalized silk fibroin nanoparticles as a prospective drug delivery system.

Silk fibroin nanoparticles (FNP) have been increasingly investigated in biomedical fields due to their biocompatibility and biodegradability properties. To widen the FNP versatility and applications, and to control the drug release from the FNP, this study developed the Eudragit S100-functionalized FNP (ES100-FNP) as a pH-responsive drug delivery system, by two distinct methods of co-condensation and adsorption, employing the zwitterionic furosemide as a model drug. The particles were characterized by sizes and zeta potentials (DLS method), morphology (electron microscopy), drug entrapment efficiency and release profiles (UV-Vis spectroscopy), and chemical structures (FT-IR, XRD, and DSC). The ES100-FNP possessed nano-sizes of ∼200-350 nm, zeta potentials of ∼ -20 mV, silk-II structures, enhanced thermo-stability, non-cytotoxic to the erythrocytes, and drug entrapment efficiencies of 30%-60%, dependent on the formulation processes. Interestingly, the co-condensation method yielded the smooth spherical particles, whereas the adsorption method resulted in durian-shaped ones due to furosemide re-crystallization. The ES100-FNP adsorbed furosemide via physical adsorption, followed Langmuir model and pseudo-second-order kinetics. In the simulated oral condition, the particles could protect the drug in the stomach (pH 1.2), and gradually released the drug in the intestine (pH 6.8). Remarkably, in different pH conditions of 6.8, 9.5, and 12, the ES100-FNP could control the furosemide release rates depending on the formulation methods. The ES100-FNP made by the co-condensation method was mainly controlled by the swelling and corrosion process of ES100, and followed the Korsmeyer-Peppas non-Fickian transport mechanism. Whereas, the ES100-FNP made by the adsorption method showed constant release rates, followed the zero-order kinetics, due to the gradual furosemide dissolution in the media. Conclusively, the ES100-FNP demonstrated high versatility as a pH-responsive drug delivery system for biomedical applications.

Photocatalytic degradation of methylene blue under visible light by cobalt ferrite nanoparticles/graphene quantum dots.

A simple approach was developed to synthesize cobalt ferrite nanoparticles/graphene quantum dots (CF/GQDs). The material was prepared from a homogeneous mixture of iron nitrate, cobalt nitrate, and starch at 140, 180 and 200 °C in a 24 h thermal hydrolysis process. The obtained materials were characterised by using X-ray diffraction, scanning electron microscopy, transmission electron microscopy, ultraviolet-visible diffuse reflectance spectroscopy, Fourier-transform infrared spectroscopy, photoluminescence spectroscopy, vibrating-sample magnetometry, and nitrogen adsorption/desorption isotherms. Cobalt ferrite crystals of around 8-10 nm and graphene quantum dots formed directly at 200 °C. Stacking GQDs sheets onto the CF nanoparticles resulted in CF/GQDs nanoparticles. The nanocomposite exhibits satisfactory fluorescent and superparamagnetic properties, which are vital for catalytic applications. The CF/GQDs catalyse significantly the degradation of methylene blue (MB) under visible light. The catalyst can be recycled with an external magnetic field and displays suitable stability. Also, it was reused in three successive experiments with a loss of efficiency of about 5%. The CF/GQDs are considered as an efficient photocatalyst for MB degradation and other dyes.

An ensemble multi-scale framework for long-term forecasting of air quality.

The significance of accurate long-term forecasting of air quality for a long-term policy decision for controlling air pollution and for evaluating its impacts on human health has attracted greater attention recently. This paper proposes an ensemble multi-scale framework to refine the previous version with ensemble empirical mode decomposition (EMD) and nonstationary oscillation resampling (NSOR) for long-term forecasting. Within the proposed ensemble multi-scale framework, we on one hand apply modified EMD to produce more regular and stable EMD components, allowing the long-range oscillation characteristics of the original time series to be better captured. On the other hand, we provide an ensemble mechanism to alleviate the error propagation problem in forecasts caused by iterative implementation of NSOR at all lead times and name it improved NSOR. Application of the proposed multi-scale framework to long-term forecasting of the daily PM2.5 at 14 monitoring stations in Hong Kong demonstrates that it can effectively capture the long-term variation in air pollution processes and significantly increase the forecasting performance. Specifically, the framework can, respectively, reduce the average root-mean-square error and the mean absolute error over all 14 stations by 8.4% and 9.2% for a lead time of 100 days, compared to previous studies. Additionally, better robustness can be obtained by the proposed ensemble framework for 180-day and 365-day long-term forecasting scenarios. It should be emphasized that the proposed ensemble multi-scale framework is a feasible framework, which is applicable for long-term time series forecasting in general.

Fabrication and characterization of a NiO-ZnO/PANI-CNTs composite for sensing of methanol in an aqueous environment.

In this study, we fabricated a composite of NiO-ZnO/PANI-CNTs on a fluorine tin oxide (FTO) electrode and examined the electrochemical sensing behavior of the modified electrode to detect methanol in aqueous solution. The structural, morphological, and electrochemical properties of the composite were characterized using various methods such as X-ray diffraction (XRD), EDS, FTIR, X-ray photoelectron spectroscopy (XPS), field-emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), selected area electron diffraction (SAED), and electrochemical techniques such as cyclic voltammetry (CV) and chronoamperometry (CA). The composite-based electrode showed excellent electrocatalytic activity and selectivity for methanol oxidation. The calibration equation obtained was ΔI = 0.0003 × CMeOH + 0.02811, with a high correlation coefficient of 0.9993, over a wide detection range of 0 to 500 mM. The material exhibits great potential for the fabrication of sensors to detect methanol in commercial products. Real gasoline samples have been selected to evaluate the practical performance and feasibility of this as-prepared sensor. The experimental data indicated that the recovery of gasoline samples is about 98%, indicating this to be an appropriate detection procedure for effective electrochemical determination of MeOH in real gasoline samples.

Chemical compositions and biological activities of Serevenia buxifolia essential oil leaves cultivated in Vietnam (Thua Thien Hue).

Serevenia buxifolia is an evergreen citrus plant and has attracted considerable attention due to its bioactive components and biological activities. In the present study, the essential oil (EO) from S. buxifolia cultivated in Vietnam was demonstrated to exhibit the in vitro antioxidant, thrombolytic, anti-hemolysis, anti-inflammatory, and antidiabetic activities. Briefly, the gas chromatography coupled to mass spectrometry analysis revealed that the leaf EO of S. buxifolia was composed of 33 components, with the main constituents being ß-carypphyllene (32.5%), and elixene (9.8%). The extracted oil possessed a fairly high free radical scavenging activity against 2, 2-diphenyl-1-picrylhydrazyl (DPPH), with an IC50 value of 190.7 µg/mL compared with positive control, α-tocopherol, IC50 value of 42.6 µg/mL. The EO also exhibited thrombolytic activity: the percentage of inhibition was found to be 70.75% at 100 µL, in comparison with 87.2% for the positive control, streptokinase. For hemolytic activity, the percentage of inhibition of the EO was from 27.4% to 59.6% at concentrations from 10 to 100 µg/mL, respectively. The results of in vitro anti-inflammatory activity indicated that the EO of S. buxifolia leaves effectively protects the heat-induced denaturation, with an IC50 value of 40.25 µg/mL. The EO also exhibited antidiabetic potential, with IC50 values of 87.8 and 134.9 µg/mL against α-amylase and α-glucosidase, respectively. It is noteworthy that the potent biological activities of the obtained S. buxifolia oil increased in a dose-dependent manner. The results achieved show that the EO of S. buxifolia leaves can be a potential source for oxidative stress, inflammatory, and diabetic management.

Stable biogenic silver nanoparticles from Syzygium nervosum bud extract for enhanced catalytic, antibacterial and antifungal properties.

In the present study, the biosynthesis of stable silver nanoparticles (BioAgNPs) was accomplished successfully for the first time by using an aqueous extract derived from the buds of Syzygium nervosum (SN) as both a reducing and a stabilizing agent. Transmission electron microscopy (TEM) and high-resolution transmission electron microscopy (HR-TEM) investigations revealed that the biosynthesized BioAgNPs were predominantly spherical with an average size of 10-30 nm. It was found that the outstanding stability of the BioAgNPs colloidal solution was assigned to the additive effect of the surrounding protective organic layer and the highly negatively charged surface of the nanoparticles. Consequently, good antibacterial activity was demonstrated by the colloidal BioAgNPs solution against four distinct bacterial strains, including Gram-positive S. aureus and B. subtilis as well as Gram-negative E. coli and S. typhi. Interestingly, the biosynthesized BioAgNPs displayed greater antibacterial activity even when tested at low doses against Gram-negative S. typhi. In addition, the biogenic AgNPs demonstrated a significant level of catalytic activity in the process of converting 2-NP, 3-NP, and 4-NP into aminophenols within 15 min, with reaction rate constants of 9.0 × 10-4, 10 × 10-4, and 9.0 × 10-4 s-1, respectively. BioAgNPs formulations were assessed against anthracnose disease in tea plants and were found to be as effective as the positive control at a dose of 20-fold dilution, but less effective at a dose of 30-fold dilution. Both doses of BioAgNPs formulations significantly suppressed Colletotrichum camelliae (anthracnose disease) without affecting the growth of the tea plants.

Assessing cognitive decline in Vietnamese older adults using the Montreal Cognitive Assessment-Basic (MoCA-B) and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) during the COVID-19 pandemic: A feasibility study.

Objectives: The lack of cognitive assessment tools suitable for people with minimal formal education is a barrier to identify cognitive impairment in Vietnam. Our aims were to (i) evaluate the feasibility of conducting the Montreal Cognitive Assessment-Basic (MoCA-B) and Informant Questionnaire On Cognitive Decline in the Elderly (IQCODE) remotely on the Vietnamese older adults, (ii) examine the association between the two tests, (iii) identify demographic factors correlated with these tools. Methods: The MoCA-B was adapted from the original English version, and a remote testing procedure was conducted. One hundred seventy-three participants aged 60 and above living in the Vietnamese southern provinces were recruited via an online platform during the COVID-19 pandemic. Results: IQCODE results showed that the proportions of rural participants classified as having mild cognitive impairment and dementia were substantially higher than those in urban areas. Levels of education and living areas were associated with IQCODE scores. Education attainment was also the main predictor of MoCA-B scores (30% of variance explained), with an average of 10.5 points difference between those with no formal education and those who attended university. Conclusions: It is feasible to administer the IQCODE and MoCA-B remotely in the Vietnamese older population. Education attainment played a stronger role in predicting MoCA-B scores than IQCODE, suggesting the influence of this factor on MoCA-B scores. Further study is needed to develop socio-culturally appropriate cognitive screening tests for the Vietnamese population.

Assessment of the distribution and ecological risks of heavy metals in coastal sediments in Vietnam's Mong Cai area.

Coastal sediments in the Mong Cai area were collected and analyzed for grain size, heavy metals, total organic carbon, and isotopes (210Pb, 226Ra, δ15N, δ13C) to assess sediment quality. The most common sediments were fine sand in surface sediment, very fine sand in core C1, and very coarse and coarse silt in core C2. The total organic carbon was highest in C2 next to the surface and lowest in C1, with content levels of 1.81%, 0.40%, and 0.31%, respectively. The chronology in C1 was 1877-2019 (142 years, 0-5 0 cm), with an average sedimentation rate of 0.71 cm/year. In C2, the chronology was 1944-2019 (75 years, 0-14 cm), with an average sedimentation rate of 0.27 cm/year. These δ13C and δ15N in the sediment reflect the source of the organic matter mix from the marine and terrigenous sediments. All studied heavy metals were lower than the ISQGs, with the exception of As in C1 and C2, which were higher. C1 showed a decline in As over time, while C2 As levels increased between 1996 and 2019. In terms of heavy metal pollution indexes, the geoaccumulation index (Igeo) showed that C1 and C2 were unpolluted to moderately polluted with As, with Li and Pb in C2; the enrichment factor (EF) was moderately enriched with As; the contamination factor (CF) was moderately contaminated (Pb, Cd, Fe, Mo, and Li) in C2 and C1 (Cd, As, Li) and considerably contaminated (As) in C2. The risk factor (ER) of As showed a moderate potential ecological risk in C2. The degree of contamination (CD) ranged from moderate to considerable (C1, C2), and the ecological risk (RI) was low. Although CD ranged from moderate (C1) to considerable (C2), most contamination was concentrated at the bottom of the cores. RI was low. The Mong Cai sediment quality does not currently affect the coastal area's ecosystem and fauna.

Characterization and Complete Genomic Analysis of Vibrio Parahaemolyticus-Infecting Phage KIT05.

Vibrio parahaemolyticus is a bacterial pathogen in marine aquaculture systems and a major cause of food-borne illnesses worldwide. In the present study, Vibrio phage KIT05 was isolated from water collected from a shrimp farm in the Mekong Delta, Vietnam. It was characterized based on its morphology, growth curve, lytic properties, and genome sequence. Under the electron microscope, KIT05 particles had an icosahedral head with a diameter of 62.3 nm and a short tail of 24.1 nm. The one-step growth curve of KIT05 showed that its latency time was approximately 40 min and burst size was 18 plaque-forming units/cell. The genome of KIT05 comprises 50,628 bp with a GC content of 41.63%. It contains 60 open reading frames that are encoded within both strands and four tRNAs. The presence of direct terminal repeats of 130 bp at both ends of the KIT05 DNA was determined. According to phage morphology, genomic organization, and phylogeny analysis, Vibrio phage KIT05 was classified into the family Podoviridae. The genome annotation revealed that KIT05 had no virulent or lysogenic genes. This study may help identify a novel candidate for developing biocontrol agents for Vibrio parahaemolyticus.

An Information-Entropy Position-Weighted K-Mer Relative Measure for Whole Genome Phylogeny Reconstruction.

Alignment methods have faced disadvantages in sequence comparison and phylogeny reconstruction due to their high computational costs in handling time and space complexity. On the other hand, alignment-free methods incur low computational costs and have recently gained popularity in the field of bioinformatics. Here we propose a new alignment-free method for phylogenetic tree reconstruction based on whole genome sequences. A key component is a measure called information-entropy position-weighted k-mer relative measure (IEPWRMkmer), which combines the position-weighted measure of k-mers proposed by our group and the information entropy of frequency of k-mers. The Manhattan distance is used to calculate the pairwise distance between species. Finally, we use the Neighbor-Joining method to construct the phylogenetic tree. To evaluate the performance of this method, we perform phylogenetic analysis on two datasets used by other researchers. The results demonstrate that the IEPWRMkmer method is efficient and reliable. The source codes of our method are provided at https://github.com/ wuyaoqun37/IEPWRMkmer.

Heterogeneous Types of miRNA-Disease Associations Stratified by Multi-Layer Network Embedding and Prediction.

Abnormal miRNA functions are widely involved in many diseases recorded in the database of experimentally supported human miRNA-disease associations (HMDD). Some of the associations are complicated: There can be up to five heterogeneous association types of miRNA with the same disease, including genetics type, epigenetics type, circulating miRNAs type, miRNA tissue expression type and miRNA-target interaction type. When one type of association is known for an miRNA-disease pair, it is important to predict any other types of the association for a better understanding of the disease mechanism. It is even more important to reveal associations for currently unassociated miRNAs and diseases. Methods have been recently proposed to make predictions on the association types of miRNA-disease pairs through restricted Boltzman machines, label propagation theories and tensor completion algorithms. None of them has exploited the non-linear characteristics in the miRNA-disease association network to improve the performance. We propose to use attributed multi-layer heterogeneous network embedding to learn the latent representations of miRNAs and diseases from each association type and then to predict the existence of the association type for all the miRNA-disease pairs. The performance of our method is compared with two newest methods via 10-fold cross-validation on the database HMDD v3.2 to demonstrate the superior prediction achieved by our method under different settings. Moreover, our real predictions made beyond the HMDD database can be all validated by NCBI literatures, confirming that our method is capable of accurately predicting new associations of miRNAs with diseases and their association types as well.

Effects of solvent-solvent fractionation on the total terpenoid content and in vitro anti-inflammatory activity of Serevenia buxifolia bark extract.

Severinia buxifolia (Rutaceae) is often used as a traditional medical plant. The present study was carried out to estimate the effects of solvents (petroleum ether and hexane: ethyl acetate) used in liquid-liquid extraction to total terpenoid content (TTC) and in vitro anti-inflammatory activity of the extracts obtained from S. buxifolia bark. The results showed that solvent fractionation increased the TTC compared with crude extracts. The hexane: ethyl acetate bark extract fraction (HEF) had the highest TTC (731.48 µg/ml) in comparison with the petroleum ether bark extract fraction (PEF) (564.81 µg/ml) and the crude extract (CE) (184.26 µg/ml). In addition, one of composition of terpenoid of S. buxifolia, namely ursolic acid, was determined by HPLC method from the crude CE and the fractions PEF and HEF: 2.44 µg/g DW, 3.56 µg/g DW and 5.04 µg/g DW, respectively. The samples had an in vitro anti-inflammatory activity comparable with that of two reference standards (aspirin and indomethacin). Particularly, the HEF fraction had the highest in vitro anti-inflammatory activity (i.e., albumin denaturation: IC50 = 147.91 µg/mL, heat-induced hemolysis: IC50 = 159.91 µg/mL, proteinase inhibition: IC50 = 117.72 µg/mL, and lipoxygenase activity: IC50 = 90.45 µg/mL). Besides, the preliminary experiments of this study were conducted to determine the influences of maceration factors (solvent type, temperature, and time) for S. buxifolia bark extract. The TTC ranged from 453.70 to 842.59 mg linalool/g DW, and the extraction yield from 2.40% to 5.120% in all extracts. Based on TTC and EY, the hexane: acetone mixture is recommended as the optimal solvent to obtain the crude bark extract (CE) at 46°C for 24 hr of maceration. Extracts of S. buxifolia bark are a promising source for the treatment of inflammatory diseases.

Long- and short-term time series forecasting of air quality by a multi-scale framework.

Air quality forecasting for Hong Kong is a challenge. Even taking the advantages of auto-regressive integrated moving average and some state-of-the-art numerical models, a recently-developed hybrid method for one-day (two- and three-day) ahead forecasting performs similarly to (slightly better than) a simple persistence forecasting. Long-term forecasting also remains an important issue, especially for policy decision for better control of air pollution and for evaluation of the long-term impacts on public health. Given the well-recognized negative effects of PM2.5, NO2 and O3 on public health, we study their time series under the multi-scale framework with empirical mode decomposition and nonstationary oscillation resampling to explore the possibility of long-term forecasting and to improve short-term forecasts in Hong Kong. Applied to a dataset from January 2016 to December 2018, the long-term forecasting (with lead time about 100 days) of the multi-scale framework has the root-mean-square error (RMSE) comparable with that of the short-term (with lead time of one or two days) forecasting by the persistence method, while its improvement for short-term forecasting (with lead time of one, two or three days) is quite substantial over the persistence forecasting, with RMSEs reduced by respectively 44%-47%, 30%-45%, and 40%-60% for PM2.5, NO2, and O3. Compared to the hybrid method, it turns out that, for short-term forecasting for the same data, the multi-scale framework can reduce RMSE by about 25% (respectively 30%) for PM2.5 (respectively NO2 and O3). In addition, we find no significant difference in the forecasting performance of the multi-scale framework among different types of stations. The multi-scale framework is feasible for time series forecasting and applicable to other pollutants in other cities.

Phylogenetic Analysis of HIV-1 Genomes Based on the Position-Weighted K-mers Method.

HIV-1 viruses, which are predominant in the family of HIV viruses, have strong pathogenicity and infectivity. They can evolve into many different variants in a very short time. In this study, we propose a new and effective alignment-free method for the phylogenetic analysis of HIV-1 viruses using complete genome sequences. Our method combines the position distribution information and the counts of the k-mers together. We also propose a metric to determine the optimal k value. We name our method the Position-Weighted k-mers (PWkmer) method. Validation and comparison with the Robinson-Foulds distance method and the modified bootstrap method on a benchmark dataset show that our method is reliable for the phylogenetic analysis of HIV-1 viruses. PWkmer can resolve within-group variations for different known subtypes of Group M of HIV-1 viruses. This method is simple and computationally fast for whole genome phylogenetic analysis.

Multi-term time fractional diffusion equations and novel parameter estimation techniques for chloride ions sub-diffusion in reinforced concrete.

In this paper, searching for a better chloride ions sub-diffusion system, a multi-term time-fractional derivative diffusion model is proposed for the description of the time-dependent chloride ions penetration in reinforced concrete structures exposed to chloride environments. We prove the stability and convergence of the model. We use the modified grid approximation method (MGAM) to estimate the fractional orders and chloride ions diffusion coefficients in the reinforced concrete for the multi-term time fractional diffusion system. And then to verify the efficiency and accuracy of the proposed methods in dealing with the fractional inverse problem, two numerical examples with real data are investigated. Meanwhile, we use two methods of fixed chloride ions diffusion coefficient and variable diffusion coefficient with diffusion depth to simulate chloride ions sub-diffusion system. The result shows that with the new fractional orders and parameters, our multi-term fractional order chloride ions sub-diffusion system is capable of providing numerical results that agree better with the real data than other models. On the other hand, it is also noticed from the numerical solution of the chloride ions sub-diffusion system that setting the variable diffusion coefficient with diffusion depth is more reasonable. And it is also found that chloride ions diffusion coefficients in reinforced concrete should be decreased with diffusion depth which is completely consistent with the theory. In addition, the model can be used to predict the chloride profiles with a time-dependent property. This article is part of the theme issue 'Advanced materials modelling via fractional calculus: challenges and perspectives'.

Physical activity and sedentary behaviour during pregnancy are associated with gestational weight gain in Vietnamese women.

BACKGROUND AND OBJECTIVES: Gestational weight gain is known to impact maternal and child health outcomes. Energy intake and energy expenditure are major components of clinical nutrition in relation to weight gain during pregnancy. The study was to determine the association of physical activity and sitting time during pregnancy with gestational weight gain in Vietnamese women. METHODS AND STUDY DESIGN: A multicentre prospective cohort study was conducted in Vietnam from 2015 to 2017. A total of 1873 women with a singleton pregnancy were included. Physical activity and sitting exposures during pregnancy were determined using an interviewer-administered validated questionnaire. Multiple regression analysis was performed to assess physical activity and sitting time in relation to gestational weight gain, adjusting for the confounding effects of maternal characteristics and total energy intake during pregnancy. RESULTS: The mean weight gain was 12.9 (Standard deviation 4.1) kg throughout pregnancy. Pregnant women with prolonged sitting time gained an average of 0.6 kg more weight (p=0.016 for highest versus lowest tertiles). Conversely, women who were physically active, in terms of having higher tertiles of total physical activity, moderate-to-vigorous-intensity, household/ caregiving activities, and occupational physical activity, experienced significantly less gestational weight gain (p<0.05 for highest versus lowest tertiles). CONCLUSIONS: Inverse associations were found between gestational weight gain and physical activity (i.e. intensities and several domains), whereas gestational weight gain tended to increase with longer sitting time. Therefore, being physically active and less sedentary is important to regulate weight gain during pregnancy.

Multifractal temporally weighted detrended cross-correlation analysis of multivariate time series.

Fractal and multifractal properties of various systems have been studied extensively. In this paper, first, the multivariate multifractal detrend cross-correlation analysis (MMXDFA) is proposed to investigate the multifractal features in multivariate time series. MMXDFA may produce oscillations in the fluctuation function and spurious cross correlations. In order to overcome these problems, we then propose the multivariate multifractal temporally weighted detrended cross-correlation analysis (MMTWXDFA). In relation to the multivariate detrended cross-correlation analysis and multifractal temporally weighted detrended cross-correlation analysis, an innovation of MMTWXDFA is the application of the signed Manhattan distance to calculate the local detrended covariance function. To evaluate the performance of the MMXDFA and MMTWXDFA methods, we apply them on some artificially generated multivariate series. Several numerical tests demonstrate that both methods can identify their fractality, but MMTWXDFA can detect long-range cross correlations and simultaneously quantify the levels of cross correlation between two multivariate series more accurately.

Postpartum Physical Activity and Weight Retention within One Year: A Prospective Cohort Study in Vietnam.

After delivery, mothers are encouraged to increase physical activity (PA) gradually to regulate body weight; however, data on PA in relation to postpartum weight retention remains scarce, particularly among Asian women. In a cohort of 1617 Vietnamese mothers, we investigated the prospective association between habitual PA exposures at 3-month postpartum and weight retention at 6-month and 12-month postpartum. Detailed information on PA intensity and domains was collected from participants using a validated instrument specifically for Vietnamese women. Linear regression analyses and a general linear model for the repeated weight retention measures were used to ascertain the apparent relationships. On average, the participants reported 3.6 (SD 3.9) and 2.6 (SD 3.8) kg weight loss at 6- and 12-month postpartum, respectively. Total and light-intensity PA were inversely associated with the postpartum weight retention (p for trend <0.05). Our findings highlight the importance of resuming PA in the early postpartum period as an appropriate weight management strategy.

Prevalence and pregnancy outcomes of gestational diabetes mellitus by different international diagnostic criteria: a prospective cohort study in Vietnam.

Background: Several diagnostic criteria for gestational diabetes mellitus (GDM) have been developed and used internationally. This study estimated the prevalence of GDM and pregnancy outcomes among Vietnamese women.Methods: A prospective cohort study of 2030 women was undertaken in Vietnam between 2015 and 2016. Baseline interview and a single-step 75-g oral glucose tolerance test (OGTT) were conducted at 24-28 weeks of gestation. GDM was defined by five international diagnostic criteria: America Diabetes Association (ADA), European Association for the Study of Diabetes (EASD), International Association of the Diabetes and Pregnancy study groups (IADPSG), National Institute of Health and Clinical Excellence (NICE), and World Health Organization (WHO). Maternal and neonatal outcomes were assessed using medical records. Besides descriptive statistics and univariate analyses, logistic regressions were performed to ascertain the associations between GDM and maternal and neonatal outcomes.Results: The prevalence of GDM varied considerably by the diagnostic criteria: 6.4% (ADA), 7.9% (EASD), 22.8% (IADPSG/WHO), and 24.2% (NICE). Women with GDM according to EASD were more likely to have macrosomic infants (adjusted odds ratio (OR) 4.35, 95% confidence interval [CI]: 1.49-12.72), despite no apparent increase in risk under other criteria. Babies born to mothers with GDM appeared to be large-for-gestational age (LGA) by ADA criteria (adjusted OR 2.10, 95% CI: 1.10-4.02) or EASD criteria (adjusted OR 2.15, 95% CI: 1.16-3.98), when compared to their counterparts in the normal group. No significant differences in maternal and other neonatal outcomes were found between the normal and GDM groups.Conclusions: A global guideline is needed for the diagnosis, prevention and management of GDM.